1254 Inference Jobs - Page 10

At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions. In quality engineering at PwC, you will focus on implementing leading practice standards of quality in software development and testing processes. In this field, you will use your experience to identify and resolve defects, optimise performance, and enhance user experience. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills. As part of the AI Engineering team you will design, develop, and scale AI-driven web applications and platforms. As a Senior Associate you will analyze complex problems, mentor others, and maintain rigorous standards while building meaningful client connections and navigating increasingly complex situations. This role is well-suited for engineers eager to blend their entire stack development skills with the emerging world of AI and machine learning in a fast-paced, cross-functional environment. Responsibilities Design and implement AI-driven web applications and platforms Analyze complex challenges and develop impactful solutions Mentor junior team members and foster their professional growth Maintain exemplary standards of quality in every deliverable Build and nurture meaningful relationships with clients Navigate intricate situations and adapt to evolving requirements Collaborate in a fast-paced, cross-functional team environment Leverage broad stack development skills in AI and machine learning projects What You Must Have Bachelor's Degree in Computer Science, Software Engineering, or a related field 4-9 years of experience Oral and written proficiency in English required What Sets You Apart Bachelor's Degree in Computer Science, Engineering Skilled in modern frontend frameworks like React or Angular Demonstrating hands-on experience with GenAI applications Familiarity with LLM orchestration tools Understanding of Responsible AI practices Experience with DevOps tools like Terraform and Kubernetes Knowledge of MLOps capabilities Security experience with OpenID Connect and OAuth2 Experience in AI/ML R&D or cross-functional teams Preferred Knowledge/Skills Role Overview We are looking for a skilled and proactive Full Stack Engineer to join our AI Engineering team. You will play a pivotal role in designing, developing, and scaling AI-driven web applications and platforms. This role is ideal for engineers who are passionate about blending full stack development skills with the emerging world of AI and machine learning, and who thrive in cross-functional, fast-paced environments. Key Responsibilities Develop and maintain scalable web applications and APIs using Python (FastAPI, Flask, Django) and modern frontend frameworks (React.js, Angular.js). Build intuitive, responsive UIs using JavaScript/TypeScript, CSS3, Bootstrap, and Material UI for AI-powered products. Collaborate closely with product teams to deliver GenAI/RAG-based solutions. Design backend services for: Data pipelines (Azure Data Factory, Data Lake, Delta Lake) Model inference Embedding and metadata storage (SQL, NoSQL, Vector DBs) Optimize application performance for AI inference and data-intensive workloads. Integrate third-party APIs, model-hosting platforms (OpenAI, Azure ML, AWS SageMaker), and vector databases. Implement robust CI/CD pipelines using Azure DevOps, GitHub Actions, or Jenkins. Participate in architectural reviews and contribute to design best practices across the engineering organization. Required Skills & Experience 4–9 years of professional full-stack engineering experience. Bachelor's degree in Computer Science, Engineering, or related technical field (BE/BTech/MCA) Strong Python development skills, particularly with FastAPI, Flask, or Django. Experience with data processing using Pandas. Proficient in JavaScript/TypeScript with at least one modern frontend framework (React, Angular). Solid understanding of RESTful and GraphQL API design. Experience with at least one cloud platform: Azure: Functions, App Service, AI Search, Service Bus, AI Foundry AWS: Lambda, S3, SageMaker, EC2 Hands-on experience building GenAI applications using RAG and agent frameworks. Database proficiency with: Relational databases: PostgreSQL, SQL Server NoSQL databases: MongoDB, DynamoDB Vector stores for embedding retrieval Familiarity with LLM orchestration tools: LangChain, AutoGen, LangGraph, Crew AI, A2A, MCP Understanding of Responsible AI practices and working knowledge of LLM providers (OpenAI, Anthropic, Google PaLM, AWS Bedrock) Good To Have Skills DevOps & Infrastructure: Terraform, Kubernetes, Docker, Jenkins MLOps capabilities: model versioning, inference monitoring, automated retraining Security experience with OpenID Connect, OAuth2, JWT Deep experience with data platforms: Databricks, Microsoft Fabric Prior experience in AI/ML R&D or working within cross-functional product teams Show more Show less

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. Role Overview We are seeking a Senior Associate – AI Engineer / MLOps / LLMOps with a passion for building resilient, cloud-native AI systems. In this role, you’ll collaborate with data scientists, researchers, and product teams to build infrastructure, automate pipelines, and deploy models that power intelligent applications at scale. If you enjoy solving real-world engineering challenges at the convergence of AI and software systems, this role is for you. Key Responsibilities Architect and implement AI/ML/GenAI pipelines, automating end-to-end workflows from data ingestion to model deployment and monitoring. Develop scalable, production-grade APIs and services using FastAPI, Flask, or similar frameworks for AI/LLM model inference. Design and maintain containerized AI applications using Docker and Kubernetes. Operationalize Large Language Models (LLMs) and other GenAI models via cloud-native deployment (e.g., Azure ML, AWS Sagemaker, GCP Vertex AI). Manage and monitor model performance post-deployment, applying concepts of MLOps and LLMOps including model versioning, A/B testing, and drift detection. Build and maintain CI/CD pipelines for rapid and secure deployment of AI solutions using tools such as GitHub Actions, Azure DevOps, GitLab CI. Implement security, governance, and compliance standards in AI pipelines. Optimize model serving infrastructure for speed, scalability, and cost-efficiency. Collaborate with AI researchers to translate prototypes into robust production-ready solutions. Required Skills & Experience 4 to 9 years of hands-on experience in AI/ML engineering, MLOps, or DevOps for data science products. Bachelor's degree in Computer Science, Engineering, or related technical field (BE/BTech/MCA). Strong software engineering foundation with hands-on experience in Python, Shell scripting, and familiarity with ML libraries (scikit-learn, transformers, etc.). Experience deploying and maintaining LLM-based applications, including prompt orchestration, fine-tuned models, and agentic workflows. Deep understanding of containerization and orchestration (Docker, Kubernetes, Helm). Experience with CI/CD pipelines, infrastructure-as-code tools (Terraform, CloudFormation), and automated deployment practices. Proficiency in cloud platforms: Azure (preferred), AWS, or GCP – including AI/ML services (e.g., Azure ML, AWS Sagemaker, GCP Vertex AI). Experience managing and monitoring ML lifecycle (training, validation, deployment, feedback loops). Solid understanding of APIs, microservices, and event-driven architecture. Experience with model monitoring/orchestration tools (e.g, Kubeflow, MLflow). Exposure to LLMOps-specific orchestration tools such as LangChain, LangGraph, Haystack, or PromptLayer. Experience with serverless deployments (AWS Lambda, Azure Functions) and GPU-enabled compute instances. Knowledge of data pipelines using tools like Apache Airflow, Prefect, or Azure Data Factory. Exposure to logging and observability tools like ELK stack, Azure Monitor, or Datadog. Good to Have Experience implementing multi-model architecture, serving GenAI models alongside traditional ML models. Knowledge of data versioning tools like DVC, Delta Lake, or LakeFS. Familiarity with distributed systems and optimizing inference pipelines for throughput and latency. Experience with infrastructure cost monitoring and optimization strategies for large-scale AI workloads. It would be great if the candidate has exposure to full-stack ML/DL. Soft Skills & Team Expectations Strong communication and documentation skills; ability to clearly articulate technical concepts to both technical and non-technical audiences. Demonstrated ability to work independently as well as collaboratively in a fast-paced environment. A builder's mindset with a strong desire to innovate, automate, and scale. Comfortable in an agile, iterative development environment. Willingness to mentor junior engineers and contribute to team knowledge growth. Proactive in identifying tech stack improvements, security enhancements, and performance bottlenecks. Show more Show less

Join SADA, an Insight company as a Senior AI Engineer! Your Mission We're seeking a highly skilled and visionary Senior AI Engineer to pioneer and lead our AI initiatives, establishing a robust AI foundation across our organization. As the go-to expert, you'll be critical in architecting and implementing advanced AI-driven solutions, leveraging platforms like CCAIP , Vertex AI , and Generative AI to influence product roadmaps and drive innovation. This role focuses significantly on designing, implementing, and deploying sophisticated AI-powered solutions for Contact Centers (CCAI) for our clients, alongside building robust data solutions . You'll also provide essential technical leadership and mentorship to ensure the successful delivery of projects. Responsibilities: Solution Design & Architecture: Lead the technical design and architecture of complex AI/ML solutions, including intricate conversational AI flows. This involves deeply leveraging the Google Cloud Platform (GCP) to architect solutions within Dialogflow CX, integrating with other GCP services, and designing robust data solutions using BigQuery and other relevant tools. Provide deep technical guidance specific to the CCAI ecosystem and ensure architectural alignment with Google Cloud best practices. Hands-on Development & Deployment: Drive hands-on development and deployment of complex AI components, including advanced Conversational AI components on Google CCAI. Expertly utilize Dialogflow CX, Vertex AI (including generative AI capabilities), and GCP compute services for custom integrations. Generative AI & LLMs: Implement and integrate generative AI models and Large Language Models (LLMs), including custom development and deployment, for enhanced conversational experiences and broader AI applications. Explore multimodal use cases involving audio, video, or images. CCAI Platform Management: Lead significant projects such as Dialogflow ES to CX migrations, ensuring seamless transition and optimization of conversational agents. Integrate AI solutions with various CCaaS (Contact Center as a Service) platforms like UJET/CCAIP. Data Solutions: Architect and implement robust data pipelines and solutions using BigQuery and other relevant tools for AI model training, inference, and analytics, particularly for conversational data. Technical Leadership & Mentorship: Provide deep technical guidance and mentorship to junior engineers and developers in their areas of expertise, sharing best practices and troubleshooting techniques, and fostering a culture of knowledge sharing and continuous improvement. Pre-Sales Support Contribution: Collaborate as a lead technical expert in strategic pre-sales engagements for Google CCAI, delivering expert solution demonstrations, crafting compelling technical proposals, and conducting in-depth workshops to address complex client needs. Innovation & Research: Proactively research and evaluate the latest advancements in AI/ML, generative AI, LLMs, and particularly Google CCAI, Dialogflow CX, and Vertex AI Gen AI, to identify opportunities for solution enhancement and team knowledge sharing. Pathway to Success Our singular goal is to provide customers the best possible experience in building, modernizing, and maintaining applications in Google Cloud Platform. Your success starts by positively impacting the direction of a dynamic practice with vision and passion. You will be measured quarterly by the breadth, magnitude and quality of your contributions, your ability to estimate accurately, customer feedback at the close of projects, how well you collaborate with your peers, and the consultative polish you bring to customer interactions. As you continue to execute successfully, we will build a customized development plan together that leads you through the engineering or management growth tracks. Required Qualifications: 5+ years of experience in IT, with proven experience contributing to the design, building, and deployment of enterprise-grade AI/ML solutions, including a significant focus on contact center and conversational AI solutions. Strong understanding of AI/ML principles, natural language processing (NLP), machine learning algorithms, and deep learning architectures. Expert-level hands-on experience with Google Cloud Platform (GCP) , particularly services such as: Dialogflow CX (advanced proficiency is a must) Vertex AI (especially generative AI features, custom model deployment, Vertex AI Search) BigQuery Cloud Functions or similar serverless compute Experience with Google CCAI services and ecosystem. Hands-on experience deploying and using 3rd-party LLMs. Familiarity with AI Applications like agent builder, agent space, concepts of datastore, fine tuning (Connectors, Controls, ACLs, etc.). Strong understanding of contact center operations and technologies. Excellent communication, presentation, and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences (both technical and non-technical). Preferred Qualifications: Familiarity with Agile development methodologies. Industry certifications in relevant technologies (e.g., Google Cloud Professional Machine Learning Engineer). Experience tuning applications for non-functional requirements, i.e., usability, maintainability, scalability, availability, security, portability, etc. Exposure to relational and NoSQL datastores. Experience with API design and development (RESTful, gRPC) and strong familiarity with relevant programming languages for AI/ML development (e.g., Python). Familiarity with frontend web technologies, particularly React or Angular, for building user interfaces that integrate with AI solutions. Experience with other cloud offerings and solutions (e.g., AWS Lex, SageMaker, Lambda, or Azure Bot Service, Machine Learning). Good to have experience in: Agent Assist ML: Data Ingestion, Exploration, Transformation, and Validation ML: Model Development Frameworks ML: Specialized Modeling Areas ML: Evaluation and Monitoring About SADA An Insight company Values: We built our core values on themes that internally compel us to deliver our best to our partners, our customers and to each other. Ensuring a diverse and inclusive workplace where we learn from each other is core to SADA's values. We welcome people of different backgrounds, experiences, abilities, and perspectives. We are an equal opportunity employer. Hunger Heart Harmony Work with the best: SADA has been the largest Google Cloud partner in North America since 2016 and, for the eighth year in a row, has been named a Google Global Partner of the Year. Business Performance: SADA has been named to the INC 5000 Fastest-Growing Private Companies list for 15 years in a row, garnering Honoree status. CRN has also named SADA on the Top 500 Global Solutions Providers list for the past 5 years. The overall culture continues to evolve with engineering at its core: 3200+ projects completed, 4000+ customers served, 10K+ workloads and 30M+ users migrated to the cloud. SADA India is committed to the safety of its employees and recommends that new hires receive a COVID vaccination before beginning work . Show more Show less

Job Title: DevOps Engineer Location: Gurugram (On-site) Experience Required: 2–6 years Work Schedule: Monday to Friday, 10:30 AM – 8:00 PM (1st and 3rd Saturdays off) About Darwix AI Darwix AI is a next-generation Generative AI platform built for enterprise revenue teams across sales, support, credit, and retail. Our proprietary AI infrastructure processes multimodal data such as voice calls, emails, chat logs, and CCTV streams to deliver real-time contextual nudges, performance analytics, and AI-assisted coaching. Our product suite includes: Transform+: Real-time conversational intelligence for contact centers and field sales Sherpa.ai: Multilingual GenAI assistant offering live coaching, call summaries, and objection handling Store Intel: A computer vision solution converting retail CCTV feeds into actionable insights Darwix AI is trusted by leading organizations including IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar, and Sobha Realty. We are backed by top institutional investors and are expanding rapidly across India, the Middle East, and Southeast Asia. Key Responsibilities Design, implement, and manage scalable cloud infrastructure using AWS services such as EC2, S3, IAM, Lambda, SageMaker, and EKS Build and maintain secure, automated CI/CD pipelines using GitHub Actions, Docker, and Terraform Manage machine learning model deployment workflows and lifecycle using tools such as MLflow or DVC Deploy and monitor Kubernetes-based workloads in Amazon EKS (both managed and self-managed node groups) Implement best practices for configuration management, containerization, secrets handling, and infrastructure security Ensure system availability, performance monitoring, and failover automation for critical ML services Collaborate with data scientists and software engineers to operationalize model training, inference, and version control Contribute to Agile ceremonies and ensure DevOps alignment with sprint cycles and delivery milestones Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field 2–6 years of experience in DevOps, MLOps, or related roles Proficiency in AWS services including EC2, S3, IAM, Lambda, SageMaker, and EKS Strong understanding of Kubernetes architecture and workload orchestration in EKS environments Hands-on experience with CI/CD pipelines and GitHub Actions, including secure credential management using GitHub Secrets Strong scripting and automation skills (Python, Shell scripting) Familiarity with model versioning tools such as MLflow or DVC, and artifact storage strategies using AWS S3 Solid understanding of Agile software development practices and QA/testing workflows Show more Show less

Job Description: Embedded AI Engineer Location: Dwarka Sector 12 Delhi Job Type: Full-Time / Contract / Freelance Job Description: We are seeking a skilled and motivated Embedded AI Engineer to develop and optimize a voice assistant system on resource-constrained devices like the ESP32-S3. You will be responsible for implementing wake word detection, voice activity detection (VAD), and basic speech command recognition using Espressif's ESP-SR framework, I2S microphones, and embedded ML models. And also, they have experience in computer vision-based project through that we can monitor particular object in Realtime using thermal and normal camera. Responsibilities: - Design and implement embedded voice assistant pipelines using ESP-SR, ESP-IDF, or PlatformIO. - Integrate I2S digital microphones (e.g., INMP441, DFPlayer) with ESP32 for real-time audio capture. - Develop wake word detection, VAD, and command recognition using models like WakeNet, MultiNet, or TinyML-based solutions. - - Optimize AI models and inference for ultra-low-power operation. - Manage real-time tasks using FreeRTOS on ESP32 platforms. - Interface with peripherals like SD cards, LEDs, relays, and Wi-Fi/BLE modules. - Debug, profile, and optimize memory and performance on constrained hardware. Required Skills: - Strong proficiency in C/C++ and embedded development for ESP32. - Experience with ESP-IDF, PlatformIO, or Arduino ESP32 core. - Practical knowledge of voice processing algorithms: VAD, wake word, STT. - Experience using or modifying ESP-SR, ESP-Skainet, or custom keyword spotting models. - Familiarity with I2S, DMA, and audio pre-processing (gain control, filtering). - Understanding of FreeRTOS, low-power modes, and real-time audio handling. Preferred/Bonus Skills: - Experience with TinyML, TensorFlow Lite for Microcontrollers, or Edge Impulse. - Knowledge of Python for data preprocessing and model training. - They have knowledge and experience in computer vision (OpenCV, image processing). - They have also knowledge and experience in Deep learning/AI for vision (like CNN, YOLO or Faster-R CNN, pytorch, TensorFlow, keras) - Having Experience on Nvidia Jetson Nano/Orin based device. - Experience with Bluetooth (BLE) or Wi-Fi communication for IoT applications. - Experience in noise reduction (e.g., NSNet), echo cancellation, or ESP-DSP. Qualifications: - Bachelor's or Master's degree in Electronics, Embedded Systems, Computer Engineering, or related field. - 2+ years of experience in embedded firmware or AI on edge devices. Why Join Us? - Work on cutting-edge embedded AI products for consumer and industrial voice control. - Opportunity to shape next-gen low-power voice assistant hardware. - Flexible remote work options and tech ownership. How to Apply: Send your resume, GitHub/portfolio, and any project demos to: Email: hr@gfofireequipments.com Job Type: Full-time Pay: From ₹100,000.00 per month Schedule: Day shift Work Location: In person

Company Description NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ, is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com. Job Description The Product Design and Enhancement (PDE) team is responsible for all design-related activities of the Data Science unit at NIQ, setting up the base for Retail Index reporting. The key responsibilities of PDE associate assigned to given market include: Sample Design, Universe Estimation and other design-related projects for the Retail Index Identification of quality risks and follow up on solutions Engagement with stakeholders on scope, execution, data exchange and outcomes for assigned projects Expert-level analysis of results and presentations with insights Team work in virtual multi-country environment requiring effective communication with colleagues located in various countries Usage of dedicated software supported by ad hoc programming and data mining Identification of opportunities for innovations and tools development in the dynamic work environment Analysis of processes within the area of responsibilities with recommendations on improvements Qualifications Essential: Master’s degree in Mathematics, Statistics, Economics, Operations Research or related fields Knowledge of Microsoft Office applications Competency in at least one programming language (Python or R) Organizational skills to manage projects (time management, prioritization, deadlines) Ability to engage and communicate effectively Strong analytical and problem-solving skills Good command of English Eagerness to continuously learn and adapt to changing technologies and tools Preferable: Work experience in FMCG, Market research, consumer research or similar industries Knowledge of statistical inference and survey-based research Additional Information Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion

We are seeking an experienced Devops/ AIOps Architect to design, architect, and implement an AI-driven operations solution that integrates various cloud-native services across AWS, Azure, and cloud-agnostic environments. The AIOps platform will be used for end-to-end machine learning lifecycle management, automated incident detection, and root cause analysis (RCA). The architect will lead efforts in developing a scalable solution utilizing data lakes, event streaming pipelines, ChatOps integration, and model deployment services. This platform will enable real-time intelligent operations in hybrid cloud and multi-cloud setups. Responsibilities Assist in the implementation and maintenance of cloud infrastructure and services Contribute to the development and deployment of automation tools for cloud operations Participate in monitoring and optimizing cloud resources using AIOps and MLOps techniques Collaborate with cross-functional teams to troubleshoot and resolve cloud infrastructure issues Support the design and implementation of scalable and reliable cloud architectures Conduct research and evaluation of new cloud technologies and tools Work on continuous improvement initiatives to enhance cloud operations efficiency and performance Document cloud infrastructure configurations, processes, and procedures Adhere to security best practices and compliance requirements in cloud operations Requirements Bachelor’s Degree in Computer Science, Engineering, or related field 12+ years of experience in DevOps roles, AIOps, OR Cloud Architecture Hands-on experience with AWS services such as SageMaker, S3, Glue, Kinesis, ECS, EKS Strong experience with Azure services such as Azure Machine Learning, Blob Storage, Azure Event Hubs, Azure AKS Strong experience with Infrastructure as Code (IAC)/ Terraform/ Cloud formation Proficiency in container orchestration (e.g., Kubernetes) and experience with multi-cloud environments Experience with machine learning model training, deployment, and data management across cloud-native and cloud-agnostic environments Expertise in implementing ChatOps solutions using platforms like Microsoft Teams, Slack, and integrating them with AIOps automation Familiarity with data lake architectures, data pipelines, and inference pipelines using event-driven architectures Strong programming skills in Python for rule management, automation, and integration with cloud services Nice to have Any certifications in the AI/ ML/ Gen AI space Show more Show less

Full-time Company Description NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ, is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com. Job Description The Product Design and Enhancement (PDE) team is responsible for all design-related activities of the Data Science unit at NIQ, setting up the base for Retail Index reporting. The key responsibilities of PDE associate assigned to given market include: Sample Design, Universe Estimation and other design-related projects for the Retail Index Identification of quality risks and follow up on solutions Engagement with stakeholders on scope, execution, data exchange and outcomes for assigned projects Expert-level analysis of results and presentations with insights Team work in virtual multi-country environment requiring effective communication with colleagues located in various countries Usage of dedicated software supported by ad hoc programming and data mining Identification of opportunities for innovations and tools development in the dynamic work environment Analysis of processes within the area of responsibilities with recommendations on improvements Qualifications Essential: Master’s degree in Mathematics, Statistics, Economics, Operations Research or related fields Knowledge of Microsoft Office applications Competency in at least one programming language (Python or R) Organizational skills to manage projects (time management, prioritization, deadlines) Ability to engage and communicate effectively Strong analytical and problem-solving skills Good command of English Eagerness to continuously learn and adapt to changing technologies and tools Preferable Work experience in FMCG, Market research, consumer research or similar industries Knowledge of statistical inference and survey-based research Additional Information Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion I'm interested I'm interested Privacy Policy Show more Show less

Job Description Elevate your career as the Director of Machine Learning Engineering, where your technical expertise and visionary leadership will shape the future of AI and ML solutions. As a Director of Machine Learning Engineering at JPMorgan Chase within the Corporate Sector – Artificial Intelligence and Machine Learning (AIML) Data Platforms, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of machine learning, software engineering, and product management to spearhead multiple complex ML projects and initiatives, serving as the primary decision-maker and a catalyst for innovation and solution delivery. You will be responsible for hiring, leading, and mentoring a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable ML solutions with operational excellence. You will engage deeply in technical aspects, reviewing code, mentoring engineers, troubleshooting production ML applications, and enabling new ideas through rapid prototyping. Your passion for parallel distributed computing, big data, cloud engineering, micro-services, automation, and operational excellence will be key. Job Responsibilities Lead and manage a team of machine learning engineers, ensuring the implementation, delivery, and support of high-quality ML solutions. Collaborate with product teams to deliver tailored, AI/ML-driven technology solutions. Architect and implement distributed AI/ML infrastructure, including inference, training, scheduling, orchestration, and storage. Develop advanced monitoring and management tools for high reliability and scalability in AI/ML systems. Optimize AI/ML system performance by identifying and resolving inefficiencies and bottlenecks. Drive the adoption and execution of AI/ML Platform tools across various teams. Integrate Generative AI and Classical AI within the ML Platform using state-of-the-art techniques. Lead the entire AI/ML product life cycle through planning, execution, and future development by continuously adapting, developing new AI/ML products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth. Manage, mentor, and develop a team of AI/ML professionals in a way that promotes a culture of excellence, continuous learning, and supports their professional goals. Required Qualifications, Capabilities, And Skills Formal training or certification in software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise 12+ years of experience in engineering management with a strong technical background in machine learning. Extensive hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn). Deep expertise in Cloud Engineering (AWS, Azure, GCP) and Distributed Micro-service architecture. Experienced with Kubernetes ecosystem, including EKS, Helm, and custom operators. Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems. Strategic thinker with the ability to craft and drive a technical vision for maximum business impact. Demonstrated leadership in working effectively with engineers, data scientists, and ML practitioners. Preferred Qualifications, Capabilities, And Skills Strong coding skills and experience in developing large-scale AI/ML systems. Proven track record in contributing to and optimizing open-source ML frameworks. Recognized thought leader within the field of machine learning. Understanding & experience of AI/ML Platforms, LLMs, GenAI, and AI Agents. About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success. Show more Show less

Company Description NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ, is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com. Job Description The Product Design and Enhancement (PDE) team is responsible for all design-related activities of the Data Science unit at NIQ, setting up the base for Retail Index reporting. The key responsibilities of PDE associate assigned to given market include: Sample Design, Universe Estimation and other design-related projects for the Retail Index Identification of quality risks and follow up on solutions Engagement with stakeholders on scope, execution, data exchange and outcomes for assigned projects Expert-level analysis of results and presentations with insights Team work in virtual multi-country environment requiring effective communication with colleagues located in various countries Usage of dedicated software supported by ad hoc programming and data mining Identification of opportunities for innovations and tools development in the dynamic work environment Analysis of processes within the area of responsibilities with recommendations on improvements Qualifications Essential: Master’s degree in Mathematics, Statistics, Economics, Operations Research or related fields Knowledge of Microsoft Office applications Competency in at least one programming language (Python or R) Organizational skills to manage projects (time management, prioritization, deadlines) Ability to engage and communicate effectively Strong analytical and problem-solving skills Good command of English Eagerness to continuously learn and adapt to changing technologies and tools Preferable: Work experience in FMCG, Market research, consumer research or similar industries Knowledge of statistical inference and survey-based research Additional Information Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

About Knowdis.ai Knowdis.ai is an AI-first company specializing in e-commerce applications. We harness the power of machine learning and AI to enhance e-commerce operations, optimize customer experiences, and drive growth. If you are passionate about AI-driven product innovation, this is the perfect opportunity to make a meaningful impact. Key Responsibilities: - Infrastructure Management: Build scalable and robust infrastructure for ML models, ensuring seamless production integration. - CI/CD Expertise: Develop and maintain CI/CD pipelines with a focus on ML model deployment. - Model Deployment and Monitoring: Deploy ML models using TensorFlow Serving, Pytorch Serving, Triton Inference Server, or TensorRT and monitor their performance in production. - Collaboration: Work closely with data scientists and software engineers to transition ML models from research to production. - Security and Compliance: Uphold security protocols and ensure regulatory compliance in ML systems. Skills and Experience Required: - Proficiency in Docker and Kubernetes for containerization and orchestration. - Experience with CI/CD pipeline development and maintenance. - Experience in deploying ML models using TensorFlow Serving, Pytorch Serving, Triton Inference Server, and TensorRT. - Experience with cloud platforms like AWS, Azure, and GCP. - Strong problem-solving, communication, and teamwork skills. Qualifications: - Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field. - 4-6 years of experience in ML project management, with a recent focus on MLOps. Additional Competencies: - AI Technologies Deployment, Data Engineering, IT Performance, Scalability Testing, and Security Practices. SELECTION PROCESS: Interested Candidates are mandatorily required to apply through this listing on Jigya. Only applications received through Jigya will be evaluated further. Shortlisted candidates may be required to appear in an Online Assessment administered by Jigya on behalf of the Client. Candidates selected after the screening test will be interviewed by the Client Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 6.00 + years Salary : INR 6000000-6500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: MAM, App integration Crop.Photo is Looking for: Technical Lead for Evolphin AI-Driven MAM At Evolphin, we build powerful media asset management solutions used by some of the world’s largest broadcasters, creative agencies, and global brands. Our flagship platform, Zoom, helps teams manage high-volume media workflows—from ingest to archive—with precision, performance, and AI-powered search. We’re now entering a major modernization phase, and we’re looking for an exceptional Technical Lead to own and drive the next-generation database layer powering Evolphin Zoom. This is a rare opportunity to take a critical backend system that serves high-throughput media operations and evolve it to meet the scale, speed, and intelligence today’s content teams demand. What you’ll own Leading the re-architecture of Zoom’s database foundation with a focus on scalability, query performance, and vector-based search support Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rollout—all with aggressive timelines Skills & Experience We Expect We’re looking for candidates with 7–10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas: System Design & Architecture (3–4 yrs) Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments Led system-level design for scalable, modular AWS microservices architectures Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models Deep understanding of infrastructure observability, failure handling, and graceful degradation Database & Metadata Layer Design (3–5 yrs) Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases Comfortable evaluating trade-offs between memory, query latency, and write throughput Semantic Search & Vectors (1–3 yrs) Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases Experience tuning vector indexers for performance, memory footprint, and recall Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints) Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them Media Asset Workflow (2–4 yrs) Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC Understanding of proxy workflows in video post-production Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives Cloud-Native Architecture (AWS) (3–5 yrs) Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge Experience building serverless or service-based compute models for elastic scaling Familiarity with managing multi-region deployments, failover, and IAM configuration Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows Frontend Collaboration & React App Integration (2–3 yrs) Worked closely with React-based frontend teams, especially on desktop-style web applications Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries Experience with Electron for desktop apps How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less